Can the AI recommend products to customers?

Yes. Simple Chat’s AI can recommend products during a live conversation. It draws on what the shopper says they want, what they have been browsing, and which page they are on so suggestions stay relevant to the moment instead of feeling like a generic product dump.

Product discovery is one of the highest-value uses of storefront chat. A visitor who is unsure which variant to buy, which gift set fits a budget, or how two items compare should get the same kind of guidance a knowledgeable associate would offer — grounded in what you actually sell.

How recommendations are chosen

When a customer asks for ideas, compares options, or describes what they are looking for, the AI searches your real Shopify catalog. It weighs stated preferences — size, flavor, budget, skin type, compatibility, and similar details the shopper mentions — alongside contextual signals such as the product or collection page open in the browser.

For open-ended shopping (“surprise me,” “what should I try?”) or comparison questions, the AI typically narrows to two or three strong options rather than listing every SKU you carry. That small set is easier to decide from than a wall of links, while still giving real choice.

If the shopper names a product type (“your matcha options”) or a specific product by title, selection follows that intent: broader category interest versus a single named item. The goal is always to match how the customer framed the question.

What customers see in chat

Each recommendation links directly to the product page on your store. Shoppers can open variants, price, and availability in one click without hunting the catalog on their own.

When comparing, the AI is meant to highlight meaningful differences — format, ingredients, price tier, who each option is best for — so the message reads like guidance, not an inventory export. Links stay on your domain, which keeps the path to purchase short when the shopper is ready.

Guardrails that protect trust

Recommendations only come from products that exist in your store. The AI does not invent SKUs, brands, or items you do not sell, and it does not recommend products that are unavailable.

If inventory or catalog data does not support a confident match, it will ask clarifying questions, suggest alternatives from what you do carry, or offer to connect the shopper with your team rather than guessing. Those limits matter on high-trust categories where a wrong suggestion costs more than a slow reply.

When staff may join the conversation

Some recommendation moments still deserve a human — bespoke bundles, medical-adjacent claims you do not want automated, or VIP buyers who expect a personal touch. The AI can gather preferences and product context first, then escalate so your team starts with a clear brief instead of repeating the entire discovery chat.

How browsing context shapes suggestions

Simple Chat can use what the customer is viewing on your storefront — for example a product or collection page — as additional signal alongside what they type. Someone reading a starter kit page who asks “which refill should I get?” gets recommendations that relate to that context, not unrelated bestsellers from another category.

That combination of stated preferences, on-page context, and catalog search is what makes chat recommendations feel like in-store help rather than a random carousel. It also keeps suggestions aligned with the journey the shopper already started before opening the widget.